High-Speed Delay Scanning and Deep Learning Techniques for Spectroscopic Srs Imaging

2. The method of claim 1, wherein the CNN is a 3D U-net network that includes a 3×3×3 convolution filter.

3. The method of claim 1, wherein the CNN is a spatial-spectral residual net (SS-ResNet) that includes two parallel filters including a first convolution filter on the spatial domain and a second convolution filter on the spectral domain.

4. The method of claim 3, wherein the CNN includes a parallel convolution sublayer which includes a first convolution filter (with a (1,3,3) kernel size) for the spatial domain and a second convolution filter (with a (3,1,1) kernel size) for the spectral domain.

5. The method of claim 1, wherein image restoration further includes applying pixel-wise LASSO unmixing to suppress the crosstalk between different chemical maps, wherein unmixing is based upon a principle that at each spatial location, only a few chemical components have dominant contributions.

6. The method of claim 1, wherein images are spectroscopic SRS images.

7. The method of claim 6, wherein the images are in the fingerprint domain.